• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.227-231
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• 2007

COMS (Communication, Ocean and Meteorological Satellite) is a geostationary satellite and has been developing by KARI for communication and ocean and meteorological observations. It will be launched by ARIANE 5. Ka-band components are installed on South panel, where single solar array wing is mounted. Radiators, embedded heat pipes, external heat pipe, insulation blankets and heaters are utilized for the thermal control of the satellite. The Ka-band payload section is divided several areas based on unit operating temperature in order to optimize radiator area and maximize heat rejection capability. Other equipment for sensors and bus are installed on North panel. The ocean and meteorological sensors are installed on optical benches on the top floor to decouple thermally from the satellite. During the transfer orbit operation, satellite will be under severe thermal environments due to low dissipation of components, satellite attitudes and LAE(Liquid Apogee Engine) firing. This paper presents temperature and heater power prediction and validation of thermal control design during transfer orbit operation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.77-88
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• 2007

Axiomatic Design has been developed as a general design framework during past two decades and TRIZ has been developed for a design tool over 50 years. Axiomatic design is quite excellent in that design should be decoupled. When a design matrix is established, the characteristics of the design are identified according to the coupling properties. If the design is coupled, a decoupling process should be found. However, axiomatic design does not specifically indicate how to decouple a coupled design. In this research, the coupling manner is classified into six patterns. Each pattern could be solved by an appropriate TRIZ module. A table, which matches the coupling pattern and a TRIZ module, is proposed for effective application of the two design theories. The decoupling ideas are proposed by using TRIZ modules. When the number of decoupled designs is more than one, the engineer should select the final idea. The proposed method is applied to practical cases such as a tape feeder and a beam adjuster of the laser marker.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.340-352
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• 2022

This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x- and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.

• Journal of Aerospace System Engineering
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• v.14 no.1
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• pp.16-20
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• 2020

The fatigue happening during the road riding of the vehicle and for the moment the aircraft lands on the runway is closely related to the life cycle of the landing gear, the airframe, the vehicle's suspension, etc. The multiple loads acting on the wheel are longitudinal, lateral, vertical, and braking forces. To study the dynamic characteristics and fatigue stiffness of the vehicle, the dynamic fatigue simulator generally has been used to represent the real road vibration in the lab. It can save time and cost. In hardware, the critical factor in the hydraulic fatigue simulator structure is to decouple each axis and to endure several load vibration. In this paper, the inverse kinematic analysis method derives the magnitude of movement of the hydraulic servo actuator by the coupling after rendering the maximum movement displacement in the axial direction at the center of the dummy wheel. The result of the analysis is that the coupling between the axes is weak to reproduce the real road vibrations precisely.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of Power Electronics
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• v.14 no.2
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• pp.271-281
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• 2014

Fluctuating wind conditions necessitate the use of a variable speed wind turbine (VSWT) with a AC/DC/AC converter scheme in order to harvest the maximum power from the wind and to decouple the synchronous generator voltage and frequency from the grid voltage and frequency. In this paper, a combination of a three phase diode bridge rectifier (DBR) and a modified topology of the diode clamped multilevel inverter (DCMLI) has been considered as an AC/DC/AC converter. A control strategy has been proposed for the DCMLI to achieve the objective of grid interface of a wind power system together with local load compensation. A novel fixed frequency current control method is proposed for the DCMLI based on the level shifted multi carrier PWM for achieving the required control objectives with equal and uniform switching frequency operation for better control and thermal management with the modified DCMLI. The condition of the controller gain is derived to ensure the operation of the DCMLI at the fixed frequency of the carrier. The converter current injected into the distribution grid is controlled in accordance with the wind power availability. In addition, load compensation is performed as an added facility in order to free the source currents being fed from the grid of harmonic distortion, unbalance and a low power factor even though the load may be unbalanced, non-linear and of a poor power factor. The results are validated using PSCAD/EMTDC simulation studies.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.643-650
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• 2004

Control flow graph is used for Performing many Program-analysis techniques, such as data-flow and control-dependence analysis, and software-engineering techniques, such as program slicing and testings. For these analyses to be safe and useful, the CFG should incorporate the exception flows that are induced by exceptions. In previous research to construct control flow graph, normal flows and exception flows are computed at the same time, since these two flows are known to be mutually dependent. By investigating realistic Java programs, we found that the cases when these two flows are mutually dependent rarely happen. So, we can decouple exception flow analysis from normal flow analysis. In this paper we propose an analysis that estimates exception flows. We also propose exception flow graph to represent exception flows. And we show that the control flow graph that accounts for exception flows can be constructed by merging exception flow graph onto normal control flow graph.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2396-2402
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• 2015

Air compressor, as an essential equipment used in the factory and plant operations, accounts for around 30% of the total electricity consumption in U.S.A, thereby being proposed advanced technologies to reduce electricity consumption. When the fluctuation of the compressed airflow rate is small, the system stability is increased followed by the reduction of the electricity consumption which results in the efficient design of the energy system. In the statistical analysis, the normal distribution, log normal distribution, gamma distribution or the like are generally used to identify system characteristics. However a single distribution may not fit well the data with long tail, representing sudden air flow rate especially in extremes. In this paper, authors decouple the compressed airflow rate into two parts to present a mixture of distribution function and suggest a method to reduce the electricity consumption. This reduction stems from the fact that a general pareto distribution estimates more accurate quantile value than a gaussian distribution when an airflow rate exceeds over a large number.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.